As a Senior Data Engineer, you will:
• Design, develop, and support scalable batch and near real-time data pipelines, data products, and lakehouse-ready data assets using Spark, Python, SQL, Hive, Databricks, and cloud-native technologies.
• Build and optimize capabilities supporting the ONE Data Lake and Mastercard's unified data platform strategy.
• Develop ingestion, transformation, and orchestration solutions for batch and streaming/near real-time data patterns using technologies such as Cribl, SSIS, Apache Ozone, Cloudera Data Services, Hive, Spark, Azure, Microsoft Fabric, Databricks, and related ecosystem tools.
• Enable trusted, governed, and accessible enterprise data through the implementation of data quality, lineage, and governance standards.
• Partner closely with Product, TPM, Data Governance, Architect, and Engineering teams to deliver strategic business outcomes.
• Support AI, analytics, reporting, and decisioning use cases by delivering scalable and reliable data assets.
• Drive modernization initiatives across hybrid data environments and cloud.
• Improve operational efficiency through automation, monitoring, observability, and self-service capabilities.
• Troubleshoot complex platform and data issues, perform root cause analysis, and implement sustainable solutions.
• Evaluate emerging technologies and identify opportunities to advance Team ONE's data capabilities. Required Qualifications
• 6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.
• Solid hands-on experience with Apache Spark, Python, SQL and Databricks.
• Experience building and maintaining large-scale data pipelines and distributed data processing systems.
• Experience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.
• Experience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.
• Strong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.
• Hands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.
• Experience implementing data quality, governance, metadata, and lineage capabilities.
• Proven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.
• Strong communication and collaboration skills with the ability to work effectively across technical and business teams.
• Demonstrated ability to manage competing priorities in a fast-paced environment.
• Strong ownership mindset and commitment to delivering high-quality solutions. Responsibilities As a Senior Data Engineer, you will:
• Design, develop, and support scalable batch and near real-time data pipelines, data products, and lakehouse-ready data assets using Spark, Python, SQL, Hive, Databricks, and cloud-native technologies.




• Build and optimize capabilities supporting the ONE Data Lake and Mastercard's unified data platform strategy.
• Develop ingestion, transformation, and orchestration solutions for batch and streaming/near real-time data patterns using technologies such as Cribl, SSIS, Apache Ozone, Cloudera Data Services, Hive, Spark, Azure, Microsoft Fabric, Databricks, and related ecosystem tools.
• Enable trusted, governed, and accessible enterprise data through the implementation of data quality, lineage, and governance standards.
• Partner closely with Product, TPM, Data Governance, Architect, and Engineering teams to deliver strategic business outcomes.
• Support AI, analytics, reporting, and decisioning use cases by delivering scalable and reliable data assets.
• Drive modernization initiatives across hybrid data environments and cloud.
• Improve operational efficiency through automation, monitoring, observability, and self-service capabilities.
• Troubleshoot complex platform and data issues, perform root cause analysis, and implement sustainable solutions.
• Evaluate emerging technologies and identify opportunities to advance Team ONE's data capabilities. Required Qualifications
• 6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.
• Strong hands-on experience with Apache Spark, Python, SQL and Databricks.
• Experience building and maintaining large-scale data pipelines and distributed data processing systems.
• Experience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.
• Experience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.
• Strong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.
• Hands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.
• Experience implementing data quality, governance, metadata, and lineage capabilities.
• Proven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.
• Strong communication and collaboration skills with the ability to work effectively across technical and business teams.
• Demonstrated ability to manage competing priorities in a fast-paced environment.
• Strong ownership mindset and commitment to delivering high-quality solutions. Qualifications Required Qualifications
• 6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.
• Strong hands-on experience with Apache Spark, Python, SQL and Databricks.




• Experience building and maintaining large-scale data pipelines and distributed data processing systems.
• Experience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.
• Experience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.
• Strong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.
• Hands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.
• Experience implementing data quality, governance, metadata, and lineage capabilities.
• Proven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.
• Strong communication and collaboration skills with the ability to work effectively across technical and business teams.
• Demonstrated ability to manage competing priorities in a fast-paced environment.
• Strong ownership mindset and commitment to delivering high-quality solutions. Preferred Qualifications
• Experience with Cribl or similar observability/log streaming platforms, including data routing, filtering, enrichment, and delivery to downstream lakehouse or analytics platforms.
• Experience with Microsoft Fabric, OneLake, and cloud-native data platforms.
• Experience with enterprise data governance and metadata management solutions.
• Experience supporting analytics, reporting, AI, or machine learning workloads.
• Experience with Power BI and enterprise reporting environments.
• Experience mentoring engineers and leading technical initiatives. At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client
- a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

📌 Data Engineering offshore (Pune)
🏢 Zensar
📍 Pune